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• W2767102912 abstract "Signals are usually described in two domains: time and frequency. The Fourier transform is used for signal transformation from time domain to frequency domain and vice versa and that is enough to analyse the stationary signal. If a signal is non-stationary, the Fourier transform can be utilized to determine frequencies in signal but it can't be applied to determine the moment when a particular signal exists. For the analysis of non-stationary signals the wavelet transform can be used as well as a continuous or discrete wavelet transform. If the signal has a large number of samples, a discrete wavelet transform should be applicable preferably. If the signal is a discrete dynamic series, fast algorithms of discrete wavelet transforms can be used. The article presents 4 types of wavelets that can be applied to carry out fast discrete wavelet transforms. Based on the performed calculations the most appropriate wavelet is chosen." @default.
• W2767102912 created "2017-11-10" @default.
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• W2767102912 date "2017-05-01" @default.
• W2767102912 modified "2023-09-27" @default.
• W2767102912 title "Application of signal analysis for diagnostics" @default.
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• W2767102912 doi "https://doi.org/10.1109/icieam.2017.8076487" @default.
• W2767102912 hasPublicationYear "2017" @default.
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